Preventing workplace accidents in construction : data mining and analytics strategies
The construction industry is vital to any national economy; it is also one of the industries most susceptible to workplace incidents. The unacceptably high rates of incidents in construction have huge socio-economic consequences for the victims, their families and friends, co-workers, employers and...
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| Main Author | |
|---|---|
| Format | Electronic eBook |
| Language | English |
| Published |
Abingdon, Oxon ; New York, NY :
Routledge,
2020.
|
| Series | Spon research.
|
| Subjects | |
| Online Access | Full text |
| ISBN | 9781315110462 1315110466 9781351616133 1351616137 9781351616140 1351616145 9781351616126 1351616129 9781138087453 1138087459 |
| Physical Description | 1 online resource |
Cover
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| 003 | OCoLC | ||
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| 020 | |z 1138087459 | ||
| 024 | 7 | |a 10.1201/9781315110462 |2 doi | |
| 035 | |a (OCoLC)1105557824 | ||
| 100 | 1 | |a Kamardeen, Imriyas, |e author. | |
| 245 | 1 | 0 | |a Preventing workplace accidents in construction : |b data mining and analytics strategies / |c Imriyas Kamardeen. |
| 264 | 1 | |a Abingdon, Oxon ; |a New York, NY : |b Routledge, |c 2020. | |
| 264 | 4 | |c ©2020 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Spon research | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Curtailing construction fatalities using analytics -- Reducing uncertainties in compensation for occupational diseases in construction using analytics -- Curbing psychological injuries in construction using analytics -- Predicting and preventing secondary psychological injuries in construction using analytics. | |
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 520 | |a The construction industry is vital to any national economy; it is also one of the industries most susceptible to workplace incidents. The unacceptably high rates of incidents in construction have huge socio-economic consequences for the victims, their families and friends, co-workers, employers and society at large. Construction safety researchers have introduced numerous strategies, models and tools through scientific inquiries involving primary data collection and analyses. While these efforts are commendable, there is a huge potential to create new knowledge and predictive models to improve construction safety by utilising already existing data about workplace incidents. In this new book, Imriyas Kamardeen argues that more sophisticated approaches need to be deployed to enable improved analyses of incident data sets and the extraction of more valuable insights, patterns and knowledge to prevent work injuries and illnesses. The book aims to apply data mining and analytic techniques to past workplace incident data to discover patterns that facilitate the development of innovative models and strategies, thereby improving work health, safety and well-being in construction, and curtailing the high rate of incidents. It is essential reading for researchers and professionals in construction, health and safety and anyone interested in data analytics. | ||
| 590 | |a Knovel |b Knovel (All titles) | ||
| 650 | 0 | |a Building |x Safety measures |x Data processing. | |
| 650 | 0 | |a Building |x Accidents |x Psychological aspects. | |
| 650 | 0 | |a Psychic trauma |x Prevention. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Quantitative research. | |
| 655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
| 655 | 9 | |a electronic books |2 eczenas | |
| 776 | 0 | 8 | |i Print version: |a Kamardeen, Imriyas. |t Preventing workplace accidents in construction. |d Abingdon, Oxon ; New York, NY : Routledge, 2019 |z 9781138087453 |w (DLC) 2019012684 |w (OCoLC)1096233056 |
| 830 | 0 | |a Spon research. | |
| 856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpPWICDMA1/preventing-workplace-incidents?kpromoter=marc |y Full text |